Green Space Morphology and School Myopia in China

Abstract

Importance: China has experienced both rapid urbanization and major increases in myopia prevalence. Previous studies suggest that green space exposure reduces the risk of myopia, but the association between myopia risk and specific geometry and distribution characteristics of green space has yet to be explored. These must be understood to craft effective interventions to reduce myopia.

Objective: To evaluate the associations between myopia and specific green space morphology using novel quantitative data from high-resolution satellite imaging.

Design, setting, and participants: This prospective cohort study included students grades 1 to 4 (aged 6 to 9 years) in Shenzhen, China. Baseline data were collected in 2016-2017, and students were followed up in 2018-2019. Data were analyzed from September 2020 to January 2022.

Exposures: Eight landscape metrics were calculated using land cover data from high-resolution Gaofen-2 satellite images to measure area, aggregation, and shape of green space.

Main outcome and measures: The 2-year cumulative change in myopia prevalence at each school and incidence of myopia at the student level after 2 years were calculated as main outcomes. The associations between landscape metrics and school myopia were assessed, controlling for geographical, demographic, and socioeconomic factors. Principal component analyses were performed to further assess the joint effect of landscape metrics at the school and individual level.

Results: A total of 138 735 students were assessed at baseline. Higher proportion, aggregation, and better connectivity of green space were correlated with slower increases in myopia prevalence. In the principal component regression, a 1-unit increase in the myopia-related green space morphology index (the first principal component) was negatively associated with a 1.7% (95% CI, -2.7 to -0.6) decrease in myopia prevalence change at the school level (P = .002). At the individual level, a 1-unit increase in myopia-related green space morphology index was associated with a 9.8% (95% CI, 4.1 to 15.1) reduction in the risk of incident myopia (P < .001), and the association remained after further adjustment for outdoor time, screen time, reading time, and parental myopia (adjusted odds ratio, 0.88; 95% CI, 0.80 to 0.97; P = .009).

Conclusions and relevance: Structure of green space was associated with a decreased relative risk of myopia, which may provide guidance for construction and renovation of schools. Since risk estimates only indicate correlations rather than causation, further interventional studies are needed to assess the effect on school myopia of urban planning and environmental designs, especially size and aggregation metrics of green space, on school myopia.

Figure 1.. Overall Study Design and Participant Flow Diagram

^aLinear regression was used for the school analysis and was adjusted for percentage of male students, mean age, myopia prevalence (ie, mean spherical equivalent refraction) at baseline, student density, and school status. ^bMixed-effects logistic regression was used for the student analysis and accounted for the school clustering, adjusting for sex, age, spherical equivalent refraction at baseline, student density, and school status. ^cAdditionally adjusted for paternal myopia, maternal myopia, mean screen time, mean reading time, and mean outdoor activity time after school per day.

Figure 2.. Campus Green Space Extraction and Spatial Metrics Calculation

Using remote sensing images, school campuses (red) and surrounding 500-m buffer zones (pink) were assessed to calculate landscape metrics. For green space extraction, the threshold normalized difference vegetation index (NDVI) value for the classification of vegetation was set to 0.25, with higher values indicating green space (green) and lower values indicating nongreen area (gray). RGB indicates red, green, blue.

Figure 3.. Association Between Myopia and Percentage of Landscape

A, A higher value of percentage of landscape indicates a higher ratio of green space over the total area. B, With a 10% increase in percentage of landscape, the change in myopia rate decreased by 1.5% (95% CI, −2.5 to −0.4; P = .006).

Figure 4.. Association Between Myopia and Aggregation Index

A, A higher value of aggregation index indicates a more aggregated green space pattern. B, Higher aggregation index led to a reduction in myopia rate change (−0.3%; 95% CI, −0.5 to −0.1; P = .004).

Figure 5.. Principal Component Regression

A, The first principal component, which included the contributions from the 7 landscape metrics that were associated with myopia (ie, myopia-related green space morphology index), was the only component with an eigenvalue larger than 1 and accounted for 82.9% of the total variance. A 1-unit increase in the myopia-related green space morphology index indicates 1 SD higher in proportion of the total and largest green space patches, larger patch sizes, increased aggregation, improved connectivity, greater segmentation of green space patches, and shorter in distances between the patches. B, With the myopia-related green space morphology index increased, we observed a decrease in the changes in school myopia rate (−1.7%; 95% CI, −2.7 to −0.6; P = .002).